A review of machine learning applications in wildfire science and management
Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …
with early applications including neural networks and expert systems. Since then, the field …
Forest fire occurrence prediction in China based on machine learning methods
Forest fires may have devastating consequences for the environment and for human lives.
The prediction of forest fires is vital for preventing their occurrence. Currently, there are fewer …
The prediction of forest fires is vital for preventing their occurrence. Currently, there are fewer …
Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting
The large and catastrophic wildfires have been increasing across the globe in the recent
decade, highlighting the importance of simulating and forecasting fire dynamics in near real …
decade, highlighting the importance of simulating and forecasting fire dynamics in near real …
A new method for prediction of air pollution based on intelligent computation
S Al-Janabi, M Mohammad, A Al-Sultan - Soft Computing, 2020 - Springer
The detection and treatment of increasing air pollution due to technological developments
represent some of the most important challenges facing the world today. Indeed, there has …
represent some of the most important challenges facing the world today. Indeed, there has …
An Innovative synthesis of deep learning techniques (DCapsNet & DCOM) for generation electrical renewable energy from wind energy
S Al-Janabi, AF Alkaim, Z Adel - Soft Computing, 2020 - Springer
Renewable energy becomes one of the main resources that help the world to safety the
environment from pollution and provide the people of new type of energy; therefore, this …
environment from pollution and provide the people of new type of energy; therefore, this …
Comparisons of diverse machine learning approaches for wildfire susceptibility mapping
K Gholamnia, T Gudiyangada Nachappa… - Symmetry, 2020 - mdpi.com
Climate change has increased the probability of the occurrence of catastrophes like
wildfires, floods, and storms across the globe in recent years. Weather conditions continue to …
wildfires, floods, and storms across the globe in recent years. Weather conditions continue to …
Global wildfire susceptibility mapping based on machine learning models
Wildfires are a major natural hazard that lead to deforestation, carbon emissions, and loss of
human and animal lives every year. Effective predictions of wildfire occurrence and burned …
human and animal lives every year. Effective predictions of wildfire occurrence and burned …
Mapping China's forest fire risks with machine learning
Y Shao, Z Feng, L Sun, X Yang, Y Li, B Xu, Y Chen - Forests, 2022 - mdpi.com
Forest fires are disasters that are common around the world. They pose an ongoing
challenge in scientific and forest management. Predicting forest fires improves the levels of …
challenge in scientific and forest management. Predicting forest fires improves the levels of …
Differential evolution for feature selection: a fuzzy wrapper–filter approach
E Hancer - Soft Computing, 2019 - Springer
The selection of an optimal feature subset from all available features in the data is a vital
task of data pre-processing used for several purposes such as the dimensionality reduction …
task of data pre-processing used for several purposes such as the dimensionality reduction …
Monitoring wildfires in the northeastern peruvian amazon using landsat-8 and sentinel-2 imagery in the GEE platform
E Barboza Castillo, EY Turpo Cayo… - … International Journal of …, 2020 - mdpi.com
During the latest decades, the Amazon has experienced a great loss of vegetation cover, in
many cases as a direct consequence of wildfires, which became a problem at local, national …
many cases as a direct consequence of wildfires, which became a problem at local, national …